ABSTRACT The CDC has increasingly promoted Test & Treat (T&T) as a promising approach to prevent HIV at the population level by reducing community viral load (CVL), or the sum of all virus in a community. However, inadequate or interrupted procedures in the T&T service system generate a treatment cascade. Prior efforts to model the cascade have inadequately addressed complex and dynamic drives of CVL and city level HIV service effectiveness across the entire T&T continuum. Social, behavioral, and public health scientists increasingly call for systems science, such as system dynamics (SD) modeling, to understand and solve dynamic, complex problems like the HIV treatment cascade. This 2-year model development study, called ?Participatory System Dynamics Modeling to Simulate HIV Test-and-Treat Improvements,? is designed to build a computational and simulation model of the full HIV service system using a SD modeling approach. Communities could benefit from participating with researchers to build such a model of their local T&T service system, which can elucidate time delays and feedback loops within the structure of the system that lead to non-linear patterns or unintended consequences in the behavior of the system. This model and the resulting simulation tool would allow diverse stakeholders to understand the T&T continuum as a holistic, dynamic HIV care system, to identify weaknesses and negative drivers of the system, and to project and compare future impact of different systems level intervention options through simulation without significant resource investment. We will use group model building (GMB) and multiple secondary data sources, supported by our recently funded in-depth study of the local T&T service system in Hartford, CT (R01-MH103176), to build the SD computational/simulation model of that system. Using GMB, diverse community stakeholders will work with researchers to develop, validate, and test the model. The aims are: (1) to engage a group of community stakeholders (N=20) in an iterative, participatory GMB process to develop, refine, and critique a computational SD model of Hartford's HIV T&T service system designed to simulate CVL over time in order to uncover system performance problems; (2) to combine GMB estimates, secondary data analysis (from the R01 and local/state/national epidemiological/ service utilization data), and relevant literature to calibrate/parameterize and formulate variables in the computational SD model and develop reference modes (epidemic trends) to validate the simulation model throughout the GMB process; (3) to demonstrate use of the SD computational model and web-based simulator app as a pilot analytical and practical tool that allows stakeholders to predict and compare impacts of different intervention options to reduce HIV CVL at the city/population level. The SD computational model and simulator tool may be transferrable to other cities seeking to reduce HIV CVL with modifications using local data and stakeholder input. This study lays the foundation for an R01 implementation study to test community stakeholder use of the tool to design long-term structural interventions to reduce CVL.